Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science. Most systems encountered in the real world are nonlinear and in many practical applications nonlinear models are required to achieve an adequate modeling accuracy.
Linear programming support vector regression using a wavelet kernel is discussed in U.S. Pat. No. 7,899,652 to Lu, et al. However, improved approaches to model determination for a nonlinear dynamical system are useful for numerous applications, in particular in relation to identifying the parallel model of a nonlinear dynamical system.